An Alternative Method of Component Aggregation for Computing Multidimensional Well-Being Indicators

There is considerable debate on the methods used to compute composite indicators of well-being. The fact that most of the weights of the principal sub-components of the composite indicators are equal, and that the determinants of well-being are, to a certain extent, correlated, makes the use of ranks of these sub-components in computing the country ranks of well-being indicators a valid approach. A comparison of the actual ranks with ranks computed as averages of the ranks of subcomponent indexes for three well-known indicators of well-being, Human Development Index, Legatum Prosperity Index, and Social Progress Index, shows that results are almost the same. This calls into question the use of weighted averages of actual values of sub-components, as very high values for a variable or sub-component increases a country’s relative rank, despite much lower performance on other sub-components. Our proposed approach will help achieve more robust/reliable rankings of countries and tackle the issues posed by extreme values or non-normal distributions of the sub-components variables used.